Determining driver and vehicle characteristics based on an edge-computer device

Abstract

Methods, computer-readable media, software, and apparatuses may collect, in real-time and via an edge-computing device located in a vehicle, vehicle driving event data including data indicative of driving characteristics associated with an operation of the vehicle. The edge-computing device may analyze, based on a machine learning model, characteristics of the vehicle driving event data. The edge-computing device may, based on the machine learning model, determine at least one of: a driving behavior, a driver rating, occurrence of a collision, and vehicle diagnostics, and the information may be displayed via a graphical user interface to a user in the vehicle.

Description

FIELD OF ART[0001]Aspects of the disclosure generally relate to methods and computer systems, including one or more computers particularly configured and / or executing computer software. More specifically, aspects of this disclosure relate to edge-computing systems configured to determining driving characteristics, driver rating, performing vehicle diagnostics, and detecting collisions.BACKGROUND[0002]Many vehicles include sensors and internal computer systems designed to monitor and / or control vehicle operations, driving conditions, and driving functions. Advanced vehicle systems can perform such tasks as monitoring vehicle operations, monitoring driving behavior, fuel consumption, and optimizing engine operation to achieve higher fuel efficiency, detecting and correcting a loss of traction on an icy road, and / or detecting a collision or other roadside assistance event and automatically contacting emergency services. Various vehicle-based communication systems allow vehicles to comm...

AI Technical Summary

Benefits of technology

The present invention is about a system and method for analyzing driving behavior and vehicle characteristics in real-time using an edge-computing device. The system collects data from sensors on the vehicle and uses machine learning to identify driving behavior, driver rating, occurrence of collisions, and vehicle diagnostics. The system can communicate with other vehicles and update the machine learning model based on available network data or trained data. The technical effects of the invention include improved safety and efficiency of vehicles through real-time analysis of driving behavior and vehicle characteristics.

Problems solved by technology

Generally, processing driving and / or vehicle data, and determining driving behavior, performing vehicle diagnostics, driver rating, and so forth, may be a time consuming process.

Generally, data collection and data processing are sequential and may require multiple iterations to complete, thereby delaying feedback to drivers, and / or delaying collision evasion strategies.

This may incur additional expenses and cause delays in actions that drivers may need to take.

However, central processing of data may not take into account local variations, and valuable time may be lost.

For example, the network may not be available, and / or the network may not be able to support an upload of data.

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